---
layout: page
title: Docs
subtitle: Documentation for the supported language bindings
action: Get Started
action_url: /get_started
permalink: /api/
tag: main_docs

faq_categories:
- Deployment Environments
- Model
- Speed
- Security
- Extend and Contribute to MXNet

docs:
- title: Python
  guide_link: /api/python.html
  api_link: /api/python/docs/api
  tutorial_link: /api/python/docs/tutorials
  icon: /assets/img/python_logo.svg
  tag: python
- title: Scala
  guide_link: /api/scala.html
  api_link: /api/scala/docs/api
  tutorial_link: /api/scala/docs/tutorials
  description:
  icon: /assets/img/scala_logo.svg
  tag: scala
- title: Java
  guide_link: /api/java.html
  api_link: /api/java/docs/api
  tutorial_link: /api/java/docs/tutorials
  description:
  icon: /assets/img/java_logo.svg
  tag: java
- title: Clojure
  guide_link: /api/clojure
  api_link: /api/clojure/docs/api
  tutorial_link: /api/clojure/docs/tutorials
  description:
  icon: /assets/img/clojure_logo.svg
  tag: clojure
- title: C/C++
  guide_link: /api/cpp
  api_link: /api/cpp/docs/api
  tutorial_link: /api/cpp/docs/tutorials
  description:
  icon: /assets/img/cpp_logo.svg
  tag: cpp
- title: Julia
  guide_link: /api/julia
  api_link: /api/julia/docs/api
  tutorial_link: https://mxnet.incubator.apache.org/api/julia/docs/api/#tutorials
  description:
  icon: /assets/img/julia_logo.svg
  tag: julia
- title: R
  guide_link: /api/r
  api_link: https://s3.amazonaws.com/mxnet-prod/docs/R/mxnet-r-reference-manual.pdf
  tutorial_link: /api/r/docs/tutorials
  description:
  icon: /assets/img/R_logo.svg
  tag: r
- title: Perl
  guide_link: /api/perl
  api_link: https://metacpan.org/release/AI-MXNet
  tutorial_link: /api/perl/docs/tutorials
  description:
  icon: /assets/img/perl_logo.svg
  tag: perl
---
<!--- Licensed to the Apache Software Foundation (ASF) under one -->
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<!--- to you under the Apache License, Version 2.0 (the -->
<!--- "License"); you may not use this file except in compliance -->
<!--- with the License.  You may obtain a copy of the License at -->

<!---   http://www.apache.org/licenses/LICENSE-2.0 -->

<!--- Unless required by applicable law or agreed to in writing, -->
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<!--- "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY -->
<!--- KIND, either express or implied.  See the License for the -->
<!--- specific language governing permissions and limitations -->
<!--- under the License. -->

{%- for doc in page.docs -%}
  {%- if doc.tag == 'python' -%}
    <h2>Python API</h2>
    <div class="row docs-hero">
      <div class="col-4 docs-hero-left">
        <div class="docs-card">
            <div class="docs-logo-container">
                <img class="docs-logo-image" src="{{doc.icon | relative_url}}">
            </div>
            <div class="docs-action-btn">
              <a href="{{doc.guide_link | relative_url}}"> <img src="{{'assets/img/compass.svg' | relative_url}}" class="docs-logo-docs">{{doc.title}} Guide  <span class="span-accented">›</span></a>
            </div>
            <div class="docs-action-btn">
              <a href="{{doc.tutorial_link | relative_url}}"> <img src="{{'assets/img/video-tutorial.svg' | relative_url}}" class="docs-logo-docs">{{doc.title}} Tutorials  <span class="span-accented">›</span></a>
            </div>
            <div class="docs-action-btn">
              <a href="{{doc.api_link | relative_url}}"> <img src="{{'assets/img/api.svg' | relative_url}}" class="docs-logo-docs">{{doc.title}} API Reference  <span class="span-accented">›</span></a>
            </div>
        </div>
      </div>

    <div class="col-8 docs-hero-right">
        <h4>Python-first API</h4>
        <p>MXNet provides a comprehensive and flexible Python API to serve a broad community of developers with different levels of experience and wide ranging requirements. Current efforts are focused on the
        <a href="{{doc.api_link | relative_url}}"></a>Gluon API. Gluon provides a clear, concise, and simple API for deep learning. It makes it easy to prototype, build, and train deep learning models without sacrificing training speed.</p>
        <p>You can checkout the <a href="{{'/ecosystem'|relative_url}}">rich ecosystem</a> built around Apache MXNet Gluon, including <a href="https://d2l.ai">D2L.ai</a>, <a href="https://gluon-cv.mxnet.io">GluonCV</a>,
        <a href="https://gluon-nlp.mxnet.io">GluonNLP</a> and <a href="https://gluon-ts.mxnet.io">GluonTS</a>.</p>
        <p>While most of the usability improvement around training are focused on the python API, the performance of MXNet is accessible through a variety of different language bindings, checkout their respective API and guides below!</p>
      </div>

    </div>
  {%- endif -%}
{%- endfor -%}
<h2>Other Bindings</h2>
<div class="row">
{%- for doc in page.docs -%}
  {%- if doc.tag != 'python' -%}
  <div class="col-4">
      <div class="docs-card">
          <div class="docs-logo-container">
              <img class="docs-logo-image" src="{{doc.icon | relative_url}}">
          </div>
          <div class="docs-action-btn">
            <a href="{{doc.guide_link | relative_url}}"> <img src="{{'assets/img/compass.svg' | relative_url}}" class="docs-logo-docs">{{doc.title}} Guide  <span class="span-accented">›</span></a>
          </div>
          <div class="docs-action-btn">
            <a href="{{doc.tutorial_link | relative_url}}"> <img src="{{'assets/img/video-tutorial.svg' | relative_url}}" class="docs-logo-docs">{{doc.title}} Tutorials  <span class="span-accented">›</span></a>
          </div>
          <div class="docs-action-btn">
            <a href="{{doc.api_link | relative_url}}"> <img src="{{'assets/img/api.svg' | relative_url}}" class="docs-logo-docs">{{doc.title}} API Reference  <span class="span-accented">›</span></a>
          </div>
      </div>
  </div>
  {%- endif -%}
{%- endfor -%}
</div>
</div> <!-- closing outer wrapper -->
<div class="docs-architecture">
    <div class="wrapper">
        <h2>MXNet Architecture</h2>
        <p>
        Building a high-performance deep learning library
        requires many systems-level design decisions.
        In this design note, we share the rationale
        for the specific choices made when designing _MXNet_.
        We imagine that these insights may be useful
        to both deep learning practitioners
        and builders of other deep learning systems.
        </p>
        <h4>Deep Learning System Design Concepts</h4>
        <p>
        The following pages address general design concepts for deep learning systems.
        Mainly, they focus on the following 3 areas:
        abstraction, optimization, and trade-offs between efficiency and flexibility.
        Additionally, we provide an overview of the complete MXNet system.
        </p>
        <ul>
        {%- for p in site.pages -%}
          {%- if p.category == 'architecture' -%}
            <li><a href="{{p.url | relative_url}}">{{p.title}}</a></li>
          {%- endif -%}
        {%- endfor -%}
        </ul>
    </div>
</div>
<div class="docs-faq">
    <div class="wrapper">
        <h2>FAQ</h2>
        <ul>
        {%- for faq_c in page.faq_categories -%}
            <h3>{{faq_c}}</h3>
            {%- for p in site.pages -%}
                {%- if p.faq_c == faq_c -%}
                  <li><a href="{{p.url | relative_url}}">{{p.question}}</a></li>
                {%- endif -%}
            {%- endfor -%}
            <br>
        {%- endfor -%}
        </ul>
    </div>
</div>
<div> <!-- reopening to close wrapper -->
